US20150234549A1 - Relationship visualizations - Google Patents
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Abstract
Description
- Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57.
- This application claims benefit of U.S. Provisional Patent Application Ser. No. 61/942,540 entitled “Relationship Visualizations” filed Feb. 20, 2014, which is hereby incorporated by reference in its entirety.
- This application is related to but does not claim priority from U.S. Pat. No. 8,489,623 entitled “Creating Data In A Data Store Using A Dynamic Ontology” filed May 12, 2011, which is hereby incorporated by reference in its entirety and referred to herein as the “Ontology reference.”
- This application is related to but does not claim priority from U.S. patent application Ser. No. 13/968,265 entitled “Generating Data Clusters With Customizable Analysis Strategies” filed Aug. 15, 2013, and U.S. patent application Ser. No. 13/968,213 entitled “Prioritizing Data Clusters With Customizable Scoring Strategies” filed Aug. 15, 2013, which are hereby incorporated by reference in their entireties and collectively referred to herein as the “Cluster references.”
- In the area of computer-based platforms, relationship visualizations may be accelerated and/or generated.
- The systems, methods, and devices described herein each have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of this disclosure, several non-limiting features will now be discussed briefly.
- In some embodiments, a computer system for providing relationship visualizations comprises an object storage device. The object storage device may store information regarding a plurality of objects and properties of respective objects. The computer system may further comprise one or more hardware processors programmed via executable code instructions. When executed, the executable code instructions may cause the computer system to receive, from a user of the computer system, a selection of a plurality of objects. When further executed, the executable code instructions may cause the computer system to determine, based on input from the user or default settings, an action associated with the plurality of objects to include in a visualization. When further executed, the executable code instructions may cause the computer system to identify, in the object storage device, a plurality of the determined actions associated with respective objects. When further executed, the executable code instructions may cause the computer system to determine a first time unit associated with each of a plurality of sections of a first axis. When further executed, the executable code instructions may cause the computer system to determine a second time unit associated with each of a plurality of sections of a second axis. The first time unit may comprise a plurality of the second time units and each section of the first axis may intersect with a plurality of sections of the second axis. When further executed, the executable code instructions may cause the computer system to assign respective first time periods to each of the sections of the first axis based on the determined first time unit and respective second time periods to each of the section of the second axis based on the determined second time unit. For each identified action associated with respective objects, further executed code instructions may cause the computer system to determine, based on one or more properties of the respective object stored in the object storage device, an action time associated with the identified action. For each identified action associated with respective objects, further executed code instructions may cause the computer system to determine a first time period that includes the action time. For each identified action associated with respective objects, further executed code instructions may cause the computer system to determine a second time period that includes the action time. For each identified action associated with respective objects, further executed code instructions may cause the computer system to increment a count of actions associated with the determined first time period and the determined second time period. When further executed, the executable code instructions may cause the computer system to generate user interface data. The generated user interface data may be configured to display the visualization including indicators of the first time periods on respective sections of the first axis. The generated user interface data may be further configured to display the visualization including indicators of the second time periods on respective sections of the second axis. The generated user interface data may be further configured to display the visualization including count indicators at intersections of first time periods and second time periods. The count indicators may correspond to respective counts of actions associated with the respective first time period and second time period.
- In some embodiments, a method for providing relationship visualizations may comprise receiving, from a user of a computer system comprising a hardware computer processor, a selection of a plurality of objects. The method may further comprise determining, based on input from the user or default settings, an action associated with the plurality of objects to include in a visualization. The method may further comprise identifying, by the computer system, a plurality of the determined actions associated with respective objects. The method may further comprise determining, by the computer system, a first time unit associated with each of a plurality of sections of a first axis. The method may further comprise determining, by the computer system, a second time unit associated with each of a plurality of sections of a second axis, wherein the first time unit comprises a plurality of the second time units and each section of the first axis intersects with a plurality of sections of the second axis. The method may further comprise assigning, by the computer system, respective first time periods to each of the sections of the first axis based on the determined first time unit and respective second time periods to each of the section of the second axis based on the determined second time unit. The method may further comprise, for each identified action associated with respective objects, determining, by the computer system, based on one or more properties of the respective object, an action time associated with the identified action. The method may further comprise, for each identified action associated with respective objects, determining, by the computer system, a first time period that includes the action time. The method may further comprise, for each identified action associated with respective objects, determining, by the computer system, a second time period that includes the action time. The method may further comprise, for each identified action associated with respective objects, incrementing, by the computer system, a count of actions associated with the determined first time period and the determined second time period. The method may further comprise, generating, by the computer system, user interface data. The generated user interface data may be configured to display the visualization including indicators of the first time periods on respective sections of the first axis. The generated user interface data may be further configured to display the visualization including indicators of the second time periods on respective sections of the second axis. The generated user interface data may be further configured to display the visualization including count indicators at intersections of first time periods and second time periods. The count indicators may correspond to respective counts of actions associated with the respective first time period and second time period.
- In some embodiments, a non-transitory computer storage comprises instructions for causing a computer system to provide relationship visualizations. When executed, the code instructions may cause the computer system to receive, from a user of the computer system, a selection of a plurality of objects. When further executed, the code instructions may cause the computer system to determine, based on input from the user or default settings, an action associated with the plurality of objects to include in a visualization. When further executed, the code instructions may cause the computer system to identify a plurality of the determined actions associated with respective objects. When further executed, the code instructions may cause the computer system to determine a first time unit associated with each of a plurality of sections of a first axis. When further executed, the code instructions may cause the computer system to determine a second time unit associated with each of a plurality of sections of a second axis. The first time unit may comprise a plurality of the second time units and each section of the first axis may intersect with a plurality of sections of the second axis. When further executed, the code instructions may cause the computer system to assign respective first time periods to each of the sections of the first axis based on the determined first time unit and respective second time periods to each of the section of the second axis based on the determined second time unit. For each identified action associated with respective objects, further executed code instructions may cause the computer system to determine, based on one or more properties of the respective object, an action time associated with the identified action. For each identified action associated with respective objects, further executed code instructions may cause the computer system to determine a first time period that includes the action time. For each identified action associated with respective objects, further executed code instructions may cause the computer system to determine a second time period that includes the action time. For each identified action associated with respective objects, further executed code instructions may cause the computer system to increment a count of actions associated with the determined first time period and the determined second time period. When further executed, the code instructions may cause the computer system to generate user interface data. The generated user interface data may be configured to display the visualization including indicators of the first time periods on respective sections of the first axis. The generated user interface data may be further configured to display the visualization including indicators of the second time periods on respective sections of the second axis. The generated user interface data may be further configured to display the visualization including count indicators at intersections of first time periods and second time periods. The count indicators may correspond to respective counts of actions associated with the respective first time period and second time period.
- Certain aspects of the disclosure will become more readily appreciated as those aspects become better understood by reference to the following detailed description, when taken in conjunction with the accompanying drawings.
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FIG. 1 is a block diagram illustrating an example relationship matrix system, according to some embodiments of the present disclosure. -
FIG. 2 is a flowchart illustrating a relationship matrix generation process, according to some embodiments of the present disclosure. -
FIG. 3A illustrates an example relationship matrix, according to some embodiments of the present disclosure. -
FIG. 3B illustrates an example relationship matrix configured to update the units for the axes, according to some embodiments of the present disclosure. -
FIG. 3C illustrates an example relationship matrix configured to update time periods, according to some embodiments of the present disclosure. -
FIG. 3D illustrates an example relationship matrix configured to update its alignment, according to some embodiments of the present disclosure. -
FIG. 3E illustrates an example relationship matrix following alignment user interaction, according to some embodiments of the present disclosure. -
FIG. 3F illustrates an example relationship matrix configured to update the units of an axis, according to some embodiments of the present disclosure. -
FIG. 3G illustrates an example relationship matrix configured to update the units of both axes, according to some embodiments of the present disclosure. -
FIG. 4 illustrates an example relationship matrix configured to display an outliers view, according to some embodiments of the present disclosure. -
FIG. 5A , illustrates an example user interface of the relationship matrix system for loading and/or viewing data objects, according to some embodiments of the present disclosure. -
FIG. 5B illustrates an example user interface of the relationship matrix system for selecting data objects to generate a matrix, according to some embodiments of the present disclosure. -
FIG. 6 is a block diagram illustrating an example relationship matrix system with which various methods and systems discussed herein may be implemented. - Relationship visualizations may be accelerated and/or generated. For example, a heat map is one type of relationship visualization that may be generated to display relationships through color, saturation, gradient, and/or hue.
- Disclosed herein are systems, methods, techniques, and devices for accelerating relationship visualizations related to one or more data objects and/or properties of those data objects. Using the techniques and systems described herein, efficient, flexible, scalable, navigable, and accelerated relationship visualizations may be achieved. In one particular example implementation of the systems and methods discussed herein, data objects and/or the relationships of data objects may be displayed through a matrix visualization where some relationships are displayed through gradient, color, hue, and/or saturation. In some embodiments, the relationship matrix may comprise a time matrix. A subset of the data objects and/or a time period for display may be determined automatically by the relationship matrix system. Furthermore, the relationship matrix system may receive user interaction data to allow navigable, efficient, and/or accelerated relationship matrices.
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FIG. 1 illustrates a relationship matrix system, according to some embodiments of the present disclosure. In the example embodiment ofFIG. 1 , thematrix environment 190 comprises anetwork 160, arelationship matrix system 100, auser computing device 102, and anobject storage device 130. Various communications between these devices are illustrated. For example, communication of adata selection 110,user interaction 120,object data 140, and arelationship matrix 300 are illustrated in various actions 1-5 that are illustrated in the circled numbers inFIG. 1 . In this embodiment, therelationship matrix system 100 includes aninteraction processor 104 and arelationship matrix generator 108, each of which is described in further detail below. - In some embodiments, the
matrix environment 190 may not comprise a network. For example, theuser computing device 102, therelationship matrix system 100, and/or theobject storage device 130 may reside on the same computing device. - As shown in
FIG. 1 , at action one, adata selection 110 is transmitted from theuser computing device 102 to theinteraction processor 104 of therelationship matrix system 100. The data selection may occur through a user interface.FIG. 5A , for example, illustrates anexample user interface 500 of a software application configured to display data objects and to allow the user to select one or more of the data objects. Theexample user interface 500 comprises asearch box 502, anobject display area 504, and amenu bar 506. A human operator, e.g., the user of theuser computing device 102 ofFIG. 1 , by typing and/or entering data into thesearch box 502 may load, lookup, and/or retrieve one or more data objects. For example, by typing the name of a person, such as “John Doe,” theperson object 510 may be displayed in theobject display area 504. The other person objects 512 (includingobjects person object 510. For example, a human operator may select theperson object 510 and select an option to display associates and/or persons related to theperson object 510. Thelinks person object 510 and related person objects 512A, 512B, and/or 512C, respectively. For example, the person objects 412 may be related to the person object 410, such as, but not limited to, associates, acquaintances, and/or family members. Thelinks person object 510 and related person objects 512A, 512B, and/or 512C, respectively. For example, link 514B may display that there were 10 meetings betweenperson object 510 andrelated person object 512B. Thelinks user interface 500 may be capable of displaying any type of data object and/or may not be limited to displaying person and meeting data objects. - In some embodiments, the data objects in the
object display area 504 may be selectable through mouse clicks, touch input, and/or any other input mechanism. - In some embodiments, the
user interface 500 may display objects and/or other data in clusters, which may correspond to the systems, methods, and/or techniques disclosed in the Ontology and/or Cluster references. - In addition to visually searching and/or showing data objects and/or relationships between data objects, the
user interface 500 may allow various other manipulations. For example, data objects may be inspected (e.g., by viewing properties and/or associated data of the data objects), filtered (e.g., narrowing the universe of objects into sets and subsets by properties or relationships), and statistically aggregated (e.g., numerically summarized based on summarization criteria), among other operations and visualizations. - When a human operator has loaded the data objects, the user may then generate a relationship matrix from some or all of those data objects and/or from related data objects. For example,
FIG. 5B illustrates theuser interface 500 ofFIG. 5A comprising a matrix menu option to generate a matrix based on the loaded data objects (such as the one or more of the data objects displayed in this embodiment). In this example, the human operator has the option of selecting the “All Objects”menu item 524A or the “Selected Objects”menu item 524B by accessing the “View”menu 520, selecting the “Matrix”menu item 522, and then choosing a matrix menu item 524. For example, a matrix may be generated from all of the data objects presented by the user interface when the “All Objects”menu item 524A is selected. In some embodiments, theuser interface 500 may allow the human operator to select individual and/or one or more groups of data objects, whether or not those objects remain viewable in thedisplay area 404. Thus, upon selecting the “Selected Objects”menu item 524B a matrix may be generated from the selected data objects and/or related data objects. Theexample user interface 500 allows the human operator to send adata selection 110 to theinteraction processor 104 and/or therelationship matrix system 100 ofFIG. 1 through selecting and/or loading of data objects and/or selection of menu items 524. - Returning to
FIG. 1 , theinteraction processor 104 may receive thedata selection 110 from theuser computing device 102 through thenetwork 160. Theinteraction processor 104 may then process thedata selection 110. For example, theinteraction processor 104 may identify and/or interpret the data objects selected fromFIG. 5B . At action two, theinteraction processor 104 may then send data, including the interpreted, modified, and/orunmodified data selection 110, to therelationship matrix generator 108. At action three, therelationship matrix generator 108 may request, receive, and/or load information and/or data regarding the data objects, such as, but not limited to, objectdata 140, identified in thedata selection 110 and/or related to thedata selection 110 from theobject storage device 130. - In some embodiments, the relationship matrix system may determine one or more additional data objects based on the one or more selected objects. For example, meeting objects and/or event objects for a selected person object may be determined programmatically, such as by using techniques discussed in the Cluster references. For example, the selected person data object, which may correspond to the data selection 1110 of
FIG. 1 , may be a starting point to determine one or more additional related data objects. The additional related data objects may then be processed by the relationship matrix system. - The
relationship matrix generator 108 may generate therelationship matrix 300 from the requested and/or receivedobject data 140, which is discussed further with reference toFIG. 2 . At action four, therelationship matrix 300 may be sent to theuser computing device 102 through thenetwork 160. For example,FIG. 3A illustrates anexample relationship matrix 300. Therelationship matrix 300 ofFIG. 3A may have been generated from the selected data objects ofFIG. 5B and/or related data objects. Therelationship matrix 300 may comprise a time matrix. The relationship blocks 312 (includingblocks vertical axis 302 and the X and/orhorizontal axis 304. For example, theblock 312A may represent a relationship between “7 AM” on the X axis and “Thur” on the Y axis. In the example, the intersection at blocks 312 between the X and Y axes may correspond to the meeting objects that were shown inFIG. 5B . The gradient, color, hue, and/or saturation at blocks 312 may further represent and/or indicate relationships between the X and/or Y axes and/or display summary information regarding the objects being represented. For example, block 312A may be a darker and/or more concentrated color, hue, and/or saturation than block 312B. In the example, a darker and/or more concentrated color, hue, and/or saturation may represent a greater number of objects and/or instances at a particular intersection. Therefore, there may be more meetings and/or events at Thursday at 7 AM than Wednesday at 6 AM as indicated byblock 312A in comparison to block 312B becauseblock 312A may be a darker and/or more concentrated color, hue, and/or saturation than block 312B. - The
relationship matrix 300 may display other relationship information and/or data and/or accelerate visualizations of relationships. Therelationship matrix 300 may display a portion and/or subselection of the selected data objects fromFIG. 5B . For example, themacro unit indicator 306 may indicate a time unit that is currently being displayed. In the example, themacro unit indicator 306 may display “WEEK 2,” which may indicate to the human operator that only objects from the second week of the year are being shown. The portion and/or subselection of the selected data objects fromFIG. 5B may be determined by default settings and/or therelationship matrix generator 108 ofFIG. 1 . For example, therelationship matrix generator 108 may analyze the selected meeting objects fromFIG. 5B to determine a time period to show the highest concentration of meeting objects. The meeting objects may comprise an action time and/or event time property. The action time and/or event time property may correspond to the time at which a meeting occurred. For example, if ninety out of the one hundred meetings occurred during the second week of year, then therelationship matrix generator 108 ofFIG. 1 may determine that the second week of the year should be displayed initially as shown inFIG. 3A . In the example relationship matrix ofFIG. 3A , therelationship matrix generator 108 ofFIG. 1 may have determined that the second week of the year had the highest concentration of objects, and, therefore, displayed the second week of the year. In some embodiments, the initial time period shown may be determined by default settings. - The relationship matrix may automatically and/or based on default settings determine configurations and/or accelerate visualizations of relationships. The relationship matrix may indicate that the human operator is “BROWSING ‘Day of Week’ OF 2013 BY ‘Hour of day.’” The “Day of Week” text may comprise a
Y axis selector 308, which may allow the human operator to select different units for the Y axis. Similarly, the “Hour of Day” text may comprise anX axis selector 310, which may allow human operator to select different units for the X axis. For example, the available time units for the axes may comprise the options, such as, but not limited to: “Hour of Day,” “Day of Week,” “Day of Month,” “Week of Month,” “Month of Year.” Similar to the displayed time period, the time units of the axes that are initially displayed may be based on default settings and/or may be determined by therelationship matrix generator 108 ofFIG. 1 . Therelationship matrix generator 108 may analyze the selected and/or determined meeting objects fromFIG. 5B to determine an X time unit and/or a Y time unit to show the highest concentration of meeting objects in a time period. For example, therelationship matrix generator 108 ofFIG. 1 may have determined that “Day of Week” for the Y axis should be displayed to accelerate visualizations of relationships by the human operator. In some embodiments, therelationship matrix generator 108 ofFIG. 1 may display a subset and/or portion of the X and/or Y axes. For example,FIG. 3B illustrates anexample relationship matrix 300 with different time units. In the example, theY axis selector 308 may be set to “Day of Month” and/or theX axis selector 310 may be set to “Day of Week.” In some embodiments, thevertical ellipsis 390 along the Y axis may indicate that only the time units of February 1 through February 7 are shown. Therelationship matrix generator 108 ofFIG. 1 may have determined that the highest concentration of objects occurred in that time period and, therefore, selected the time period of February 1 through February 7 to display. In some embodiments, therelationship matrix system 100 and/or therelationship matrix generator 108 may be configured to display the lowest concentration of objects. In some embodiments, thevertical ellipsis 390 ofFIG. 3B may indicate that all of the days of the month February are displayed to the human operator. In some embodiments, therelationship matrix system 100 and/or therelationship matrix generator 108 ofFIG. 1 may automatically determine other features and/or characteristics of therelationship matrix 300 ofFIG. 3 based on the selected, determined, and/or related data objects, such as the objects fromFIG. 5B . - Returning to
FIG. 1 , at action five, the human operator may interact with therelationship matrix 300, which may cause theuser computing device 102 to senduser interaction data 120 to theinteraction processor 104 and/or therelationship matrix system 100 through thenetwork 160. For example, the human operator may interact with therelationship matrix 300 ofFIG. 3A . The human operator may select and/or change theY axis selector 308 and/orX axis selector 310 through a mouse click, touch input, and/or some other input mechanism. For example, as shown inFIG. 3B , a human operator may have changed theY axis selector 308 to “Day of Month” and/or may have changed theX axis selector 310 to “Day of week.” The change by the human operator may cause theuser computing device 102 to send theuser interaction data 120 ofFIG. 1 , which may correspond to theY axis selector 308 change and/orX axis selector 310 change. As a result, actions two, three, four, or a subset thereof, may be performed and/or repeated to generated arelationship matrix 300 as shown inFIG. 3B . For example, therelationship matrix generator 108 may receive theuser interaction data 120 and/or data based on theuser interaction data 120 from theinteraction processor 104. Therelationship matrix generator 108 may optionally request, receive, and/or load data objects from theobject storage device 130. Therelationship matrix generator 108 may then generate therelationship matrix 300, as shown inFIG. 3B , based on the user interaction of modifying theY axis selector 308 and/orX axis selector 310. -
FIG. 2 is a flowchart illustrating a relationship matrix generation process, according to some embodiments of the present disclosure. The method ofFIG. 2 may be performed by therelationship matrix system 100 ofFIG. 1 , such as the various components ofFIG. 1 that are discussed above, including therelationship matrix generator 108 and/orinteraction processor 104. Depending on the embodiment, the method ofFIG. 2 may include fewer or additional blocks and/or the blocks may be performed in order different than is illustrated. - Beginning at
block 204, data selection and/or interaction input data is received. Data selection may comprise one or more data objects selected and/or determined from the user interface. For example, user interaction input data may be received after human operator interaction illustrated inFIG. 3B and/or other interactions disclosed herein. In the example, the user interaction input data may comprise a change to theY axis selector 308 and/orX axis selector 310. - At
block 206, the interaction input data is processed. In some embodiments, the interaction input data may be transformed. Theuser interaction data 120 received from the user computing device ofFIG. 1 may comprise a format such as, but not limited to, XML, JSON, HTML response/request format, a file format that is proprietary to the relationship matrix system, or any other format. For example, theuser interaction data 120 may comprise an XML data format initially and be processed and/or transformed into another data format, such as, but not limited to, an object data format. The user interaction data may be transformed and/or incorporated into an object representing the relationship matrix user interface. Therefore, the properties of the relationship matrix, such as the user interactions, may be accessed by therelationship matrix system 100 and/orrelationship matrix generator 108 ofFIG. 1 . - At
block 208, one or more data objects and/or properties of one or more data objects are accessed. For example, a meeting object, including some or all of the properties of that meeting object, may be accessed by therelationship system 100. The meeting object may comprise one or more, time objects, time properties, a location, a link to other person data objects, and other data. In some embodiments, as previously discussed, a data object may be a starting point to load additional related data objects, such as, but not limited to, loading all the meeting and/or event objects corresponding to a person object. - At
block 210, relationship properties from the one or more data objects are identified. For example, time objects and/or time properties may comprise relationship properties that are identified. In some embodiments, relationship properties of person data objects are accessed. For example, a person data object may comprise a meetings property that comprises all of the meetings the person data object had with other person data objects. In some embodiments, actions and/or action objects may be identified for respective objects. For example, meeting objects may be determined for person objects. A time and/or action time property may be associated with the meeting objects. Thus, in one example, a user selects one or more object properties of interest (e.g., all “meeting” events associated with a particular person object), and those event objects matching the properties are located (“matched”) for inclusion in the relationship matrix. - At
block 212, the relationship matrix is generated based on the interaction input data and/or the relationship properties accessed from the data objects. For example, thematrix 300 ofFIG. 3B may be generated from user interaction data and/or relationship properties of data objects. The user interaction input data comprising the “Day of Month” selection from the Y axis input selector may be used to generate therelationship matrix 300 ofFIG. 3B . For example, since “Day of Month” was selected, the Y axis may comprise time units of days of the months, such as, February 1, 2, 3, etc., as illustrated byFIG. 3B . Similarly, the user interaction input comprising the “Day of Week” ” selection from the X axis input selector may be used to generate the labels on the X axis comprising “Sunday,” “Monday,” etc., as illustrated byFIG. 3B . The relationship blocks 320 (includingblocks FIG. 3B . Additionally, meeting data objects may be categorized by a day of the week property (e.g., Monday, Tuesday, Wednesday) and/or day of the month property (e.g., February 1, 2, etc.). The relationship blocks 320A, 320B, and/or 320C may correspond to groups of meeting data objects with time properties corresponding to the intersection of the X and Y axes. For example, the relationship block at 320A may comprise time properties corresponding to Feb. 5, 2013, which was a Tuesday. Additionally, as previously discussed, the relative gradient, color, hue, and/or saturation may correspond to the number of objects with the particular time properties at a given intersection. In the example, there may be more meeting data objects corresponding to relationship block 320A than relationship block 320B, which may correspond to the relative gradient, color, hue, and/or saturation between the two blocks. - In some embodiments, time properties may be accessed and/or used to generate the relationship matrix. For example, as discussed above, a first time period and/or second time period may be automatically determined corresponding to the time units associated with the X and/or Y axes of the generated relationship matrix. As illustrated above, time units and/or periods, such as “Day of Month,” “Month of Year,” the month “January,” and/or second week of the year, may be automatically determined to show the highest concentration of objects in the relationship matrix.
- In some embodiments, data is conceptually structured according to an object data model represented by an ontology. The conceptual data model may be independent of any particular and/or specific type of data store. For example, each object of the conceptual data model may correspond to one or more rows in a relational database, an object in an in-memory cache, and/or some combination thereof.
- In some embodiments, an ontology, as noted above, may include stored information providing a data model for storage of data in a data store. The ontology may be defined by one or more object types, which may each be associated with one or more property types. At the highest level of abstraction, a data object is a container for information representing things and/or events in the physical world. For example, a data object may represent an entity such as a person, a place, an organization, a market instrument, and/or some other noun. Data objects may represent an event that happens at a point in time and/or for a duration. Data objects may represent a document and/or other unstructured data source such as an e-mail message, a news report, a written paper, and/or a written article. Each data object may be associated with a unique identifier that uniquely identifies the data object within the data store.
- Different types of data objects may have different property types. For example, a “Person” data object may have an “Eye Color” property type and an “Event” data object may have a “Date” property type. Each property as represented by data in the data store may have a property type defined by the ontology used by the data store.
- Objects may be instantiated in the data store in accordance with the corresponding object definition for the particular object in the ontology. For example, a specific monetary payment (e.g., an object of type “event”) of US$30.00 (e.g., a property of type “currency”) taking place on 3/27/2009 (e.g., a property of type “date”) may be stored in the data store as an event object with associated currency and date properties as defined within the ontology.
- The data objects defined in the ontology may support property multiplicity. For example, a data object may be allowed to have more than one property of the same property type. For example, a “Person” data object may have multiple “Address” properties. In another example, a “Meeting” data object may have multiple “Name” properties.
- In some embodiments, the data objects the template system receives may correspond to an ontology according to the systems, methods, and/or techniques disclosed in the Ontology reference.
-
FIG. 3 (includingFIGS. 3A-3G ) illustrates example user interactions of relationship matrices. Relationship matrices may support other user interactions and the following actions are illustrative and/or non-limiting of the user interactions contemplated by the present disclosure for accelerating relationship visualizations. - In some embodiments, as previously illustrated, a human operator may change the
Y axis selector 308 and/orX axis selector 310 ofFIG. 3A to automatically update and/or generate therelationship matrix 300 ofFIG. 3B . For example, a change to theY axis selector 308 ofFIG. 3A from “Day of Week” to “Day of Month” may cause an automatic update to the labels of theY axis 302 from “Sun, Mon, etc.” to “February 1, February 2, etc.” as shown inFIG. 3B . Similarly, a change to theX axis selector 310 may cause an automatic update to the labels of theX axis 304 ofFIG. 3A to the labels ofFIG. 3B . Changes to the one or more of the axis selectors may cause other changes. For example, themacro unit indicator 306 ofFIG. 3A may change from “Week 2” to “February” as illustrated byFIG. 3B . Similarly, different relationship blocks at the intersections between theY axis 302 andX axis 304 may automatically appear and/or update following a change to one or more of the axis selectors (e.g., compare the relationship blocks 312 ofFIG. 3A with the relationship blocks 320 ofFIG. 3B ). -
FIG. 3C illustrates an example relationship matrix configured to update time periods and/or unit periods based on user interaction. For example, therelationship matrix 300 may be configured to display relationship blocks for the time period of February, as illustrated bymacro unit indicator 306. A human operator may interact through user interaction input, such as, but not limited to, touch input, mouse input, and/or any other kind of interaction input, with therelationship matrix 300 to update time periods and/or unit periods. For example, the human operator may place afinger 330, hold a mouse click, or any other input mechanism, at astarting point 332A on the relationship grid. The human operator may then drag theirfinger 330 or move the mouse to endingpoint 332B. As a result of the user interaction, the relationship matrix may update the time period and/or unit period. In the example,relationship matrix 300 may update to the month of March, which may include updating themacro unit indicator 306, the labels of theY axis 302, and/or the relationship blocks of the grid. - In some embodiments, there may be variations for updating the time periods and/or unit periods of the relationship matrix. For example, a swiping motion and/or mouse click from
point 332B to 332A may cause therelationship matrix 300 to update to the month of January (a decrement and/or change of the time period). In some embodiments, the swiping motions to increment and/or decrement the unit periods may be reversed and/or configurable by the human operator. For example, instead of the vertical swiping motion illustrated inFIG. 3C , the swiping motion may be horizontal, configurable between the two motions, and/or some combination thereof. In some embodiments, there may be a minimum and/or maximum threshold for the relative distance betweenpoints - In some embodiments, changing time periods and or unit periods may depend on the time and/or unit periods being displayed. For example, the swiping motion illustrated in
FIG. 3B may cause the week to change inFIG. 3A . “Week 2” is displayed inFIG. 3A and a swiping motion and/or mouse drag may cause the week displayed to increment or decrement to “Week 3” or “Week 1,” respectively. -
FIG. 3D illustrates an example relationship matrix configured to update the alignment of its grid based on user interaction. Similar to the touch, mouse, and/or other input mechanisms illustrated inFIG. 3C , a human operator may interact with therelationship matrix 300 to update the alignment of the grid of therelationship matrix 300 ofFIG. 3D . For example, similar to the interaction ofFIG. 3C , the human operator may drag a finger and/or hold a mouse click fromstarting point 334A to endingpoint 334B on the relationship grid ofFIG. 3D . Receipt of the horizontal input data by the relationship matrix system may cause therelationship matrix 300 to update as illustrated by the grid alignment ofFIG. 3E . -
FIG. 3E illustrates therelationship matrix 300 following the alignment user interaction ofFIG. 3D . For example, the first label of theX axis 304 is “Thursday” inFIG. 3E , which is different from the first label of theX axis 304, “Sunday,” ofFIG. 3D . The position and/or location of the relationship blocks of the relationship matrix may also update corresponding to the alignment of the grid. For example, relationship block 320C, which may have been positioned at the edge of the grid inFIG. 3D , may be re-positioned as illustrated byFIG. 3E based on the alignment interaction. The alignment motion and/or interaction fromstarting point 334A to 334B may correspond to at least three relationship block widths and/or distances. As a result, relationship block 320C and/or the corresponding label on theY axis 304 may move and/or update at least three relationship block widths and/or distances as illustrated byFIGS. 3D and 3E . - In some embodiments, there may be variations and/or additional user interactions to align and/or realign the relationship matrix. For example, a vertical user interaction, similar to the interaction illustrated by
FIG. 3C , may cause the relationship matrix to realign along the Y axis. In some embodiments, the speed and/or time between a vertical user interaction (e.g., the time between user interaction atpoints FIG. 3C ) may differentiate and/or distinguish between a time and/or unit period change ofFIG. 3C and an alignment change as illustrated byFIGS. 3D and 3E . For example, there may be a time threshold (e.g., five hundred milliseconds), where a faster movement causes a time and/or unit period change and a slower movement causes a realignment of the grid. -
FIG. 3F illustrates an example relationship matrix configured to update the units of an axis based on user interaction. For example, the human operator may placefingers points Y axis 302. The human operator may then move and/or dragfingers points relationship matrix 300 ofFIG. 3F may be “Day of Week,” the relationship matrix system may update the Y axis to “Hour of Day” to avoid the same units for both axes following user interaction input. Similar to the user interaction with fingers 340, a human operator may perform a “zooming out” action as illustrated byfingers X axis 304. The zooming out action may change and/or update the units of the X axis 304 (e.g., the X axis unit of “Day of Week” may update to “Day of Month.”) Similar to some of the illustrated user interactions in this disclosure, a zooming in and/or zooming out interaction may update the relationship blocks displayed inrelationship matrix 300, theY axis selector 308, theX axis selector 310, and/or other elements of therelationship matrix 300 accordingly. - In some embodiments, there may be some variations of updating the units of an axis of the relationship matrix. In some embodiments, the relative distance of a zooming in and/or zooming out interaction may cause different updates. For example, the zooming in action illustrated by fingers 346 may cause the X axis units to change to “Day of Month,” “Week of Month,” and/or “Month of Year” based on the relative distance dragged and/or indicated. In some embodiments, a zooming in and/or zooming out user interaction may cause the
relationship matrix 300 to update automatically. For example, as a human operator drags their fingers 346 the Y axis may update to “Day of Month,” “Week of Month,” and “Month of Year” (in that order) corresponding to the greater and/or longer distance that theirfingers 346A. Additionally, the relationship blocks shown in the relationship matrix may update automatically as the units of one or more of the axes change. - In some embodiments, the zooming in and/or zooming out actions may be configured for different results. For example, the results of actions by fingers 340 and 346 that were previously described may be reversed.
-
FIG. 3G illustrates an example relationship matrix configured to update the units of both axes simultaneously based on user interaction. The user interaction illustrated by fingers 350 (includingfinger 350A and/orfinger 350B) and their directional arrows may be similar to the zooming in action illustrated by fingers 340 ofFIG. 3F . However, one difference betweenFIGS. 3F and 3G may be the placement of fingers 350 on the grid ofrelationship matrix 300 instead of the placement of fingers on an axis. Similar to the user interaction of fingers 340 ofFIG. 3F , which may have updated one axis, the zooming in action of fingers 350 may cause both axes to update simultaneously. For example, both theY axis 302 units and theX axis 304 units may change to “Day of Week” and “Hour of Day,” respectively. Similarly, the zooming out and/or pinching motion of fingers 356 may cause both axes to update simultaneously (e.g., theY axis 302 units andX axis 304 units may change to “Week of Month” and “Day of Month,” respectively.) - In some embodiments, the variations of interactions illustrated by
FIG. 3F may be available for the zooming in and/or out interactions illustrated byFIG. 3G . For example, the relative distance of the user interaction may impact and/or affect the change in the units of the axes. In some embodiments, while the directional arrows ofFIG. 3G are shown at a diagonal, the relative orientation of the zooming in and/or zooming out actions do not matter. For example, the direction of the interactions by the fingers and/or other input mechanisms may be horizontal or vertical. - Certain of the relationship matrices illustrated herein may be configured to display a “patterns” or “outlier” view. The
relationship matrix 300 ofFIG. 3 displays a “patterns” view, while the user interface ofFIG. 4 illustrates an example of an “outliers” view. The patterns view may comprise displaying relationships with gradient, color, hue, and/or saturation. In contrast, the outliers view shown in therelationship matrix 300 ofFIG. 4 may comprise displaying relationships through one or more dots, visual indicators, and/or binary visualizations. Similar to the relationship blocks 312 ofFIG. 3A , relationship blocks 412 (includingblocks block 412B (which may be similar to the relative gradient, color, hue, and/or saturation of relationship blocks 312 ofFIG. 3A ). In the example, a greater number of dots and/or visual indicators may represent a greater number of objects and/or events at a particular intersection. - There may be advantages and/or benefits of the outliers view of a relationship matrix, such as, but not limited to, accelerating and/or facilitating human recognition of outlier relationships. In some of the previous examples, since the
relationship matrix 300 ofFIG. 3 may use a patterns view, a relationship may be difficult for a human to recognize based on relative gradient, color, hue, and/or saturation. For example, the relationship block of 312D ofFIG. 3A may be difficult for a human operator to visually recognize because the gradient, color, hue, and/or saturation may be very light and/or difficult to see on a computer monitor and/or display. The particular viewing device and/or monitor being used may affect the ability to view pattern visualizations. Therefore, with a binary relationship, dot, and/or black/white visual indicators, an outlier may be quickly recognized by a human operator. For example,relationship block 412D may comprise a single black dot, which may be easily recognized by a human operator. - In some embodiments, the relationship matrix may be configured to receive user interaction input to switch between a patterns and outliers view. For example, the
relationship matrix 300 may comprise anoutliers button 402 and apatterns button 404. A human operator may toggle between the outliers view illustrated byFIG. 4 and the patterns view illustrated byFIG. 3A by pressing, touching, and/or clicking theoutliers button 402 and thepatterns button 404, respectively. Therelationship matrix 300 may display the same relationship objects (e.g., meeting and/or event objects) but with a different view and/or representation of the relationship objects. - In some embodiments, the user interactions illustrated for the relationship matrix of
FIG. 3 may be available for the relationship matrix ofFIG. 4 . - In some embodiments, there may variations of the formulas to configure the display of the one or more dots, visual indicators, and/or binary visualizations. The number of objects to be displayed as visual indicators may be calculated by various formulas, such as, but not limited to, linear, exponential, logarithmic, any other type of equation, and/or some combination thereof. For example:
- D—Dots.
- O—Objects.
-
- In some embodiments, which use the D1 formula, if the number of objects to be displayed at a relationship block is twenty-five, three dots may be displayed. Using the same formula, if there are five objects, one dot may be displayed. Another example formula is the following:
-
D 2=CEILING(√{square root over (O)}) - In some embodiments, using the D2 formula, if the number of objects to be displayed at a relationship block is twenty-five, five dots may be displayed. Using the same formula, if there are five hundred objects, twenty-three dots may be displayed.
- In some embodiments, there may be some variations of the display of the relationship blocks illustrated as dots of
FIG. 4 and/or gradient, color, hue, and/or saturation ofFIG. 3 . The dots, gradient, color, hue, and/or saturation may be configurable by the human operator. For example, a human operator may select various hues of the color green or red to be displayed in the relationship blocks ofFIG. 3 . In other examples, a human operator may select different shapes instead of dots for the outliers view ofFIG. 4 . In some embodiments, positive and/or negative numbers may be displayed by different colors. For example, positive representations of objects as relationship blocks may be blue and/or negative representations of objects as relationship blocks may be red. - In some embodiments, the formulas and/or similar formulas for calculating outliers view representations may be used to determine representations of gradient, hue, color, and/or saturation in the patterns view.
- While some example relationship matrices of the present disclosure comprise time matrices, there may be other types of relationship matrices. In some embodiments, relationship matrices may be generated and/or accelerated where one or more axes of the relationship matrices comprises units that are hierarchical, scalar, classifications, and/or otherwise logically related and/or grouped. For example, in a time matrix, one or more axes may comprise time units such as, but not limited to, “Month of Year,” “Week of Month,” “Day of Month,” “Day of Week,” “Hour of Day.” Time units may be hierarchical because months comprise a year, days comprise a month, hours comprise a day, and so forth. In some embodiments, an axis of a relationship matrix may comprise geographical units. For example the geographical units of an axis may be the following: “Country,” “State,” “City,” “Zip Code,” and/or “Street.” Similar to the hierarchy of time units, states may comprise a country, cities may comprise a state, a city may be comprised of zip codes, and so forth. A relationship matrix and the units of the axes of a relationship matrix may be highly configurable because it may be based on a data object model and/or ontology, which may correspond to the systems, methods, and/or techniques disclosed in the Ontology reference.
- The various computing device(s) discussed herein, such as the
relationship matrix system 100 ofFIG. 1 , are generally controlled and coordinated by operating system software, such as, but not limited to, iOS, Android, Chrome OS, Windows XP, Windows Vista,Windows 7, Windows 8, Windows Server, Windows CE, Unix, Linux, SunOS, Solaris, Macintosh OS X, VxWorks, or other compatible operating systems. In other embodiments, the computing devices may be controlled by a proprietary operating system. Conventional operating systems control and schedule computer processes for execution, perform memory management, provide file system, networking, I/O services, and provide a user interface functionality, such as a graphical user interface (“GUI”), among other things. Therelationship matrix system 100 may be hosted and/or executed on one or more computing devices with one or more hardware processors and with any of the previously mentioned operating system software. -
FIG. 6 is a block diagram that illustrates example components of therelationship matrix system 100. WhileFIG. 6 refers to therelationship matrix system 100, any of the other computing devices discussed herein may have some or all of the same or similar components. - The
relationship matrix system 100 may execute software, e.g., standalone software applications, applications within browsers, network applications, etc., whether by the particular application, the operating system, or otherwise. Any of the systems discussed herein may be performed by therelationship matrix system 100 and/or a similar computing system having some or all of the components discussed with reference toFIG. 6 . - The
relationship matrix system 100 includes a bus 602 or other communication mechanism for communicating information, and a hardware processor, or multiple processors, 604 coupled with bus 602 for processing information. Hardware processor(s) 604 may be, for example, one or more general purpose microprocessors. - The
relationship matrix system 100 also includes amain memory 606, such as a random access memory (RAM), cache and/or other dynamic storage devices, coupled to bus 602 for storing information and instructions to be executed by processor(s) 604.Main memory 606 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor(s) 604. Such instructions, when stored in storage media accessible to processor(s) 604, render therelationship matrix system 100 into a special-purpose machine that is customized to perform the operations specified in the instructions. Such instructions, as executed by hardware processors, may implement the methods and systems described herein for sharing security information. - The
relationship matrix system 100 further includes a read only memory (ROM) 608 or other static storage device coupled to bus 602 for storing static information and instructions for processor(s) 604. Astorage device 610, such as a magnetic disk, optical disk, or USB thumb drive (Flash drive), etc., is provided and coupled to bus 602 for storing information and instructions. Theobject storage device 130 ofFIG. 1 may be stored on themain memory 606 and/or thestorage device 610. - In some embodiments, the
object storage device 130 ofFIG. 1 is a file system, relational database such as, but not limited to, MySql, Oracle, Sybase, or DB2, and/or a distributed in memory caching system such as, but not limited to, Memcache, Memcached, or Java Caching System, and/or some combination thereof. - The
relationship matrix system 100 may be coupled via bus 602 to adisplay 612, such as a cathode ray tube (CRT) or LCD display or touch screen, for displaying information to a computer user. Aninput device 614 is coupled to bus 602 for communicating information and command selections toprocessor 604. One type ofinput device 614 is a keyboard including alphanumeric and other keys. Another type ofinput device 614 is a touch screen. Another type of user input device iscursor control 616, such as a mouse, a trackball, a touch screen, or cursor direction keys for communicating direction information and command selections toprocessor 604 and for controlling cursor movement ondisplay 612. This input device may have two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. In some embodiments, the same direction information and command selections as cursor control may be implemented via receiving touches on a touch screen without a cursor. - The
relationship matrix system 100 may include a user interface unit to implement a GUI, for example,FIGS. 3 , 4, and/or 5, which may be stored in a mass storage device as executable software codes that are executed by the computing device(s). This and other units may include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. - The
relationship matrix system 100 and/or therelationship matrix 300 ofFIG. 1 may be configured to be compatible with web browsers such as, but not limited to, Firefox, Internet Explorer, Safari, and/or Chrome. - In general, the word “instructions,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software units, possibly having entry and exit points, written in a programming language, such as, but not limited to, Java, Lua, C, C++, or C#. A software unit may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, but not limited to, BASIC, Perl, or Python. Certain web programming methods may be used such as AJAX. It will be appreciated that software units may be callable from other units or from themselves, and/or may be invoked in response to detected events or interrupts. Software units configured for execution on computing devices by their hardware processor(s) may be provided on a computer readable medium, such as a compact disc, digital video disc, flash drive, magnetic disc, or any other tangible medium, or as a digital download (and may be originally stored in a compressed or installable format that requires installation, decompression or decryption prior to execution). Such software code may be stored, partially or fully, on a memory device of the executing computing device, for execution by the computing device. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules may be comprised of connected logic units, such as gates and flip-flops, and/or may be comprised of programmable units, such as programmable gate arrays or processors. Generally, the instructions described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage.
- The
relationship matrix system 100, or components of it, such as theinteraction processor 104 and/or therelationship matrix generator 108 ofFIG. 1 and/orFIG. 6 , may be programmed, via executable code instructions, in a programming language. - The term “non-transitory media,” and similar terms, as used herein refers to any media that store data and/or instructions that cause a machine to operate in a specific fashion. Such non-transitory media may comprise non-volatile media and/or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as
storage device 610. Volatile media includes dynamic memory, such asmain memory 606. Common forms of non-transitory media include, for example, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge, and networked versions of the same. - Non-transitory media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between nontransitory media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus 602. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.
- Various forms of media may be involved in carrying one or more sequences of one or more instructions to processor(s) 604 for execution. For example, the instructions may initially be carried on a magnetic disk or solid state drive of a remote computer. The remote computer may load the instructions into its dynamic memory and send the instructions over a telephone or cable line using a modem. A modem local to the
relationship matrix system 100 may receive the data on the telephone or cable line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on bus 602. Bus 602 carries the data tomain memory 606, from which the processor(s) 604 retrieves and executes the instructions. The instructions received bymain memory 606 may retrieve and execute the instructions. The instructions received bymain memory 606 may optionally be stored onstorage device 610 either before or after execution by processor(s) 604. - The
relationship matrix system 100 also includes acommunication interface 618 coupled to bus 602.Communication interface 618 provides a two-way data communication coupling to anetwork link 620 that is connected to alocal network 622. For example,communication interface 618 may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example,communication interface 618 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN (or WAN component to be communicated with a WAN). Wireless links may also be implemented. In any such implementation,communication interface 618 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information. - Network link 620 typically provides data communication through one or more networks to other data devices. For example,
network link 620 may provide a connection throughlocal network 622 to ahost computer 624 or to data equipment operated by an Internet Service Provider (ISP) 626.ISP 626 in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet” 628.Local network 622 andInternet 628 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals onnetwork link 620 and throughcommunication interface 618, which carry the digital data to and from therelationship matrix system 100, are example forms of transmission media. - A network, such as the
network 160 ofFIG. 1 , may comprise, but is not limited to, one or more local area networks, wide area network, wireless local area network, wireless wide area network, the Internet, or any combination thereof. - The
relationship matrix system 100 can send messages and receive data, including program code, through the network(s),network link 620 andcommunication interface 618. In the Internet example, aserver 630 might transmit a requested code for an application program throughInternet 628,ISP 626,local network 622 andcommunication interface 618. - The received code may be executed by processor(s) 604 as it is received, and/or stored in
storage device 610, or other non-volatile storage for later execution. - Each of the processes, methods, and algorithms described in the preceding sections may be embodied in, and fully or partially automated by, code instructions executed by one or more computer systems or computer processors comprising computer hardware. The processes and algorithms may be implemented partially or wholly in application-specific circuitry.
- The various features and processes described above may be used independently of one another, or may be combined in various ways. All possible combinations and subcombinations are intended to fall within the scope of this disclosure. In addition, certain method or process blocks may be omitted in some implementations. The methods and processes described herein are also not limited to any particular sequence, and the blocks or states relating thereto can be performed in other sequences that are appropriate. For example, described blocks or states may be performed in an order other than that specifically disclosed, or multiple blocks or states may be combined in a single block or state. The example blocks or states may be performed in serial, in parallel, or in some other manner. Blocks or states may be added to or removed from the disclosed example embodiments. The example systems and components described herein may be configured differently than described. For example, elements may be added to, removed from, or rearranged compared to the disclosed example embodiments.
- Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.
- Any process descriptions, elements, or blocks in the flow diagrams described herein and/or depicted in the attached figures should be understood as potentially representing units, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions may be deleted, executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those skilled in the art.
- It should be emphasized that many variations and modifications may be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure. The foregoing description details certain embodiments of the invention. It will be appreciated, however, that no matter how detailed the foregoing appears in text, the invention can be practiced in many ways. As is also stated above, it should be noted that the use of particular terminology when describing certain features or aspects of the invention should not be taken to imply that the terminology is being re-defined herein to be restricted to including any specific characteristics of the features or aspects of the invention with which that terminology is associated. The scope of the invention should therefore be construed in accordance with the appended claims and any equivalents thereof
Claims (20)
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US20170109030A1 (en) | 2017-04-20 |
US10795544B2 (en) | 2020-10-06 |
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